Furthermore, reducing cell 1009820-21-6 density, or imaging cells for a shorter period of time, will increase the fraction of cells that are accurately tracked and provide a more accurate measurement of mitotic duration in cases where such GANT61 accuracy is paramount. Other groups have developed automated or semi-automated software packages for analysis of cell division. None available for download, however, provide the functionality or ease of use that we describe here. Some packages for analysis of phase contrast movies are not fully automated, requiring partial manual analysis . Other software packages analyze cells expressing fluorescent markers such as H2B-GFP and GFP-Histone1 , but no tracking function is reported by these groups. The software from Harder et al comes closest to our package. However, their approach requires high magnification oil-objectives and use of 3 to 5 confocal z-slice acquisitions, increasing light exposure and reducing the number of fields that can be imaged in a given experiment. Held et al. also use an SVM approach to classify cells as interphase or sub-phases of mitosis, but the maximum duration of mitosis that is measured is 138 minutes, which may result in an underestimate of average mitotic duration under certain conditions. In contrast, our approach allows identification of mitotic events of longer duration, from 200 to 600 minutes, depending on imaging frequency. While Held et al. report high accuracy of their approach in determining mitotic duration, their manual analysis only included cells that were successfully tracked. Therefore, their method may be subject to the same type of selection bias that we report. Finally, DCELLIQ is the only automated analysis platform that can automatically determine interphase duration, as other methods do not track cells for a long enough period to be able to make this measurement. We conclude that, to our knowledge, our software package remains unique in terms of its ability to identify small changes in both mitotic and interphase duration using low fluorescence exposure imaging techniques in a platform that is convenient for the end user. We have shown that automated time-series analysis can be used to accurately measure mitotic and interphase duration with the need to extract far fewer features than needed with other methods. Our approach opens up new opportunities for time-lapse microscopy experiments that would otherwise be impossible to analyze due to the large amount of time necessary for manual analysis. Compared to fixed-cell analysis methods, automated analysis of time-lapse movies enables interphase and mitotic duration to be determined independently.